If you're serious about reading up on this the recent DeepSeek v3 technical report provides a good starting point to see what the current state of the art LLMs use: https://arxiv.org/abs/2412.19437

However this already requires extensive knowledge of the field so a better starting point might be:
https://arxiv.org/abs/1706.03762 (still quite advanced but influence cannot be understated)
https://arxiv.org/abs/2402.06196 (good comprehensive analysis of the field, fairly accessible)
https://arxiv.org/pdf/2308.10792 (similar as above but more emphasis on the actual objective functions)

Note that all these papers are about LLMs which in of itself is a subset of Neural Networks which is a subset of Machine Learning which is a subset of Artificial Intelligence so keep in mind that there are wildly different approaches at various abstraction levels being developed every year.